A generalized expansion matching based feature extractor

Author

Wang, Z. ; Rao, R.K. ; Nandy, D. ; Ben-Arie, Jezekiel ; Jojic, N.

Author_Institution

Dept. of Electr. & Comput. Eng., Illinois Inst. of Technol., Chicago, IL, USA

Volume

2

fYear

1996

fDate

25-29 Aug 1996

Firstpage

29

Abstract

A novel and efficient generalized feature extraction method is presented based on the expansion matching (EXM) method and the Karhunen-Loueve (KL) transform. The EXM method is used to design optimal detectors for different features. The KL representation is used to define an optimal basis for representing these EXM feature detectors with minimum truncation error. Input images are then analyzed with the resulting KL basis set. The KL coefficients obtained from the analysis are used to efficiently reconstruct the response due to any combination of feature detectors. The method is applied to real images and successfully extracts a variety of arc and edge features as well as complex junction features formed by combining two or more arc or line features

Keywords

feature extraction; transforms; Karhunen-Loueve transform; arc features; basis set; complex junction features; edge features; expansion matching method; generalized expansion matching based feature extractor; input images; minimum truncation error; optimal detectors; real images; Computer science; Computer vision; DNA computing; Detectors; Feature extraction; Finite wordlength effects; Image edge detection; Image reconstruction; Image segmentation; Shape;

fLanguage

English

Publisher

ieee

Conference_Titel

Pattern Recognition, 1996., Proceedings of the 13th International Conference on

Conference_Location

Vienna

ISSN

1051-4651

Print_ISBN

0-8186-7282-X

Type

conf

DOI

10.1109/ICPR.1996.546718

Filename

546718